| Autor: |
Hao Zhang, Fangyu Hu, Ouyang Peng, Yihui Huang, Guangli Hu, Usama Ashraf, Meifeng Cen, Xiaojuan Wang, Qiuping Xu, Chuangchao Zou, Yu Wu, Bibo Zhu, Wentao Li, Qunhui Li, Chujun Li, Chunyi Xue, Yongchang Cao |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Advanced Science, Vol 11, Iss 34, Pp n/a-n/a (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2198-3844 |
| DOI: |
10.1002/advs.202402025 |
| Popis: |
Abstract As a significant infectious disease in livestock, porcine reproductive and respiratory syndrome (PRRS) imposes substantial economic losses on the swine industry. Identification of diagnostic markers and therapeutic targets has been a focal challenge in PPRS prevention and control. By integrating metabolomic and lipidomic serum analyses of clinical pig cohorts through a machine learning approach with in vivo and in vitro infection models, lysophosphatidic acid (LPA) is discovered as a serum metabolic biomarker for PRRS virus (PRRSV) clinical diagnosis. PRRSV promoted LPA synthesis by upregulating the autotaxin expression, which causes innate immunosuppression by dampening the retinoic acid‐inducible gene I (RIG‐I) and type I interferon responses, leading to enhanced virus replication. Targeting LPA demonstrated protection against virus infection and associated disease outcomes in infected pigs, indicating that LPA is a novel antiviral target against PRRSV. This study lays a foundation for clinical prevention and control of PRRSV infections. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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